Greenhouse Gas Emissions Forecasts in Countries of the European Union by Means of a Multifactor Algorithm
Abstract
:1. Introduction
2. Materials and Methods
- Independent variables and data collection.
- Relationship of independent variables with GHGs.
- Algorithm development and validation.
- Future forecast scenarios.
2.1. Independent Variables and Data Collection
2.2. Relationship of Independent Variables with GHGs
2.3. Algorithm Development and Validation
- is the analysed variable (GDP “a”, population “b” or RES “c”);
- is the analysed MS (n = 1, 2, 3, 4, 5, 6 … 27);
- is the value of the variable for the analysed MS “”;
- is the weighting value of each variable for the analysed MS ”.
- is the amount of GHG emissions estimated for the MS “”;
- is the coefficient that represents how changes in each of the independent variables “” () influence the dependent variable “”;
- is the residual error, i.e., difference between the observed values () and those estimated by the model of the dependent variable () (Equation (3)).
- is the corrected weighting value for the MS “”.
2.4. Future Forecast Scenarios
3. Results
3.1. Algorithm and Validation
3.1.1. Weighted Values
- is the GDP in billion euros of the additional country ();
- is the population in millions of people of the additional country ();
- is the RES in percentage of the additional country ();
- is the weighting factor corresponding to the GDP of the additional country ();
- is the weighting factor corresponding to the population of the additional country ();
- is the weighting factor corresponding to the RES of the additional country ();
- is the weighting value of each variable for the analysed MS ”.
3.1.2. Standardised Coefficients
3.1.3. Corrected Weighted Factors (FPc)
- is the corrected weighting factor.
3.1.4. Final Algorithm and Validation
3.2. Future Forecast of GHG Emissions
4. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Independent Variables | Dependent Variable—GHG Emissions | ||
---|---|---|---|
Pearson Correlation Coefficient | Significance | Number of Observations | |
GDP | 0.96 | 0.000 | 27 |
Population | 0.98 | 0.000 | 27 |
RES | 0.40 | 0.021 | 27 |
Member State | GDP Growth (%) | Population Growth (%) | RES Growth (%) | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Min. | Mean | Max. | Min. | Mean | Max. | Min. | Mean | Max. | ||
1 | Austria | −4.58 | 2.55 | 4.81 | 0.39 | 0.65 | 1.35 | −0.73 | 1.25 | 4.95 |
2 | Belgium | −4.50 | 2.35 | 3.94 | 0.31 | 0.50 | 0.68 | −0.57 | 2.36 | 7.47 |
3 | Bulgaria | −0.49 | 4.88 | 9.49 | −0.73 | −0.64 | −0.53 | −2.45 | 4.42 | 11.37 |
4 | Croatia | −9.69 | 1.08 | 5.61 | −1.17 | −0.59 | −0.32 | −2.92 | 1.23 | 8.08 |
5 | Cyprus | −7.44 | 1.22 | 6.95 | −1.28 | 0.60 | 2.65 | −5.69 | 7.61 | 40.67 |
6 | Czechia | −4.35 | 3.28 | 9.41 | −0.04 | 0.21 | 0.41 | −0.76 | 5.33 | 10.29 |
7 | Denmark | 0.72 | 2.52 | 4.13 | 0.29 | 0.50 | 0.84 | 2.05 | 5.36 | 9.62 |
8 | Estonia | −3.24 | 6.25 | 13.13 | −0.38 | −0.01 | 0.43 | −2.99 | 3.26 | 12.72 |
9 | Finland | −0.78 | 2.39 | 5.24 | 0.09 | 0.32 | 0.48 | 0.57 | 2.75 | 5.46 |
10 | France | −5.22 | 1.51 | 3.16 | 0.26 | 0.42 | 0.86 | −5.55 | 3.82 | 8.69 |
11 | Greece | −9.78 | −2.90 | 2.06 | −0.75 | −0.41 | −0.06 | −4.71 | 5.79 | 19.94 |
12 | Hungary | −5.93 | 3.34 | 9.26 | −0.54 | −0.26 | −0.03 | −10.19 | 0.09 | 16.31 |
13 | Ireland | 2.19 | 8.69 | 34.80 | 0.40 | 0.87 | 1.53 | −3.67 | 4.09 | 20.75 |
14 | Italy | −7.77 | 0.33 | 2.44 | −1.10 | 0.06 | 1.84 | −11.66 | 2.80 | 22.91 |
15 | Latvia | −3.88 | 5.17 | 12.36 | −1.44 | −0.97 | −0.64 | −1.13 | 3.48 | 9.73 |
16 | Lithuania | 1.32 | 5.89 | 11.71 | −1.60 | −0.97 | 0.00 | −1.03 | 4.56 | 13.42 |
17 | Luxembourg | 2.42 | 4.24 | 5.52 | 1.92 | 2.29 | 2.56 | −3.00 | 11.23 | 45.21 |
18 | Malta | −6.98 | 6.89 | 14.23 | 0.62 | 2.25 | 4.26 | −2.59 | 13.54 | 65.15 |
19 | Netherlands | −2.03 | 2.25 | 5.05 | 0.29 | 0.48 | 0.73 | −1.63 | 10.26 | 23.06 |
20 | Poland | −1.34 | 3.86 | 9.44 | −0.12 | −0.03 | 0.02 | −5.77 | 2.23 | 16.82 |
21 | Portugal | −6.66 | 1.16 | 5.07 | −0.57 | −0.30 | 0.19 | −10.73 | −0.62 | 5.92 |
22 | Romania | −1.93 | 5.79 | 10.41 | −0.61 | −0.49 | −0.36 | −9.08 | 4.75 | 30.46 |
23 | Slovakia | −2.09 | 3.03 | 5.91 | 0.08 | 0.13 | 0.22 | −10.54 | 11.94 | 85.83 |
24 | Slovenia | −3.06 | 2.63 | 6.63 | 0.05 | 0.24 | 0.72 | −6.65 | 0.94 | 7.61 |
25 | Spain | −9.84 | 0.54 | 4.40 | −0.46 | 0.15 | 0.84 | −5.66 | 3.81 | 11.38 |
26 | Sweden | −1.95 | 2.57 | 10.18 | 0.71 | 1.00 | 1.46 | −0.50 | 1.53 | 3.62 |
Average EU−26 | −4.73 | 1.81 | 4.16 | 0.03 | 0.14 | 0.38 | 0.89 | 3.39 | 5.69 |
GHGs | Independent Factors | ||||
---|---|---|---|---|---|
(Mt CO2 eq.) | (B EUR) | (M People) | (%) | ||
1 | Austria | 81.3 | 346.8 | 8.6 | 33.2 |
2 | Belgium | 122.9 | 418.9 | 11.2 | 7.8 |
3 | Bulgaria | 60.1 | 48.5 | 7.2 | 29.9 |
4 | Croatia | 25.7 | 47.7 | 4.2 | 36.4 |
5 | Cyprus | 9.6 | 19.8 | 0.9 | 26.3 |
6 | Czechia | 130.6 | 181.5 | 10.6 | 19.0 |
7 | Denmark | 54.0 | 276.8 | 5.7 | 39.7 |
8 | Estonia | 19.3 | 21.4 | 1.3 | 48.9 |
9 | Finland | 61.1 | 215.0 | 5.5 | 51.9 |
10 | France | 475.7 | 2204.6 | 66.2 | 19.1 |
11 | Germany | 899.4 | 3037.7 | 81.5 | 13.5 |
12 | Greece | 101.7 | 184.4 | 10.9 | 26.4 |
13 | Hungary | 63.3 | 117.0 | 9.9 | 20.3 |
14 | Ireland | 62.1 | 252.4 | 4.7 | 5.8 |
15 | Italy | 457.2 | 1676.1 | 60.0 | 18.2 |
16 | Latvia | 11.3 | 24.8 | 2.0 | 51.2 |
17 | Lithuania | 20.8 | 38.8 | 2.9 | 41.8 |
18 | Luxembourg | 12.1 | 53.6 | 0.6 | 7.1 |
19 | Malta | 2.8 | 10.0 | 0.4 | 16.7 |
20 | Netherlands | 200.9 | 708.6 | 16.9 | 5.2 |
21 | Poland | 402.9 | 437.6 | 38.0 | 38.6 |
22 | Portugal | 68.8 | 186.3 | 10.4 | 26.0 |
23 | Romania | 118.8 | 168.1 | 19.8 | 25.8 |
24 | Slovakia | 41.7 | 80.4 | 5.4 | 11.2 |
25 | Slovenia | 17.8 | 40.7 | 2.1 | 33.4 |
26 | Spain | 345.5 | 1103.9 | 46.7 | 15.4 |
27 | Sweden | 56.9 | 448.0 | 9.8 | 62.3 |
Tot | Total | 12,349.34 | 443.46 | 730.87 |
Independent Factors | |||||
---|---|---|---|---|---|
1 | AU | Austria | 0.028 | 0.019 | 0.045 |
2 | BE | Belgium | 0.034 | 0.025 | 0.011 |
3 | BU | Bulgaria | 0.004 | 0.016 | 0.041 |
4 | CR | Croatia | 0.004 | 0.009 | 0.050 |
5 | CY | Cyprus | 0.002 | 0.002 | 0.036 |
6 | CZ | Czechia | 0.015 | 0.024 | 0.026 |
7 | DE | Denmark | 0.022 | 0.013 | 0.054 |
8 | ES | Estonia | 0.002 | 0.003 | 0.067 |
9 | FI | Finland | 0.017 | 0.012 | 0.071 |
10 | FR | France | 0.179 | 0.149 | 0.026 |
11 | GE | Germany | 0.246 | 0.184 | 0.018 |
12 | GR | Greece | 0.015 | 0.025 | 0.036 |
13 | HU | Hungary | 0.009 | 0.022 | 0.028 |
14 | IR | Ireland | 0.020 | 0.011 | 0.008 |
15 | IT | Italy | 0.136 | 0.135 | 0.025 |
16 | LA | Latvia | 0.002 | 0.004 | 0.070 |
17 | LI | Lithuania | 0.003 | 0.007 | 0.057 |
18 | LU | Luxembourg | 0.004 | 0.001 | 0.010 |
19 | MA | Malta | 0.001 | 0.001 | 0.023 |
20 | NE | Netherlands | 0.057 | 0.038 | 0.007 |
21 | PL | Poland | 0.035 | 0.086 | 0.053 |
22 | PO | Portugal | 0.015 | 0.023 | 0.036 |
23 | RO | Romania | 0.014 | 0.045 | 0.035 |
24 | SK | Slovakia | 0.007 | 0.012 | 0.015 |
25 | SN | Slovenia | 0.003 | 0.005 | 0.046 |
26 | SP | Spain | 0.089 | 0.105 | 0.021 |
27 | SW | Sweden | 0.036 | 0.022 | 0.085 |
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Marotta, A.; Porras-Amores, C.; Rodríguez Sánchez, A.; Villoria Sáez, P.; Masera, G. Greenhouse Gas Emissions Forecasts in Countries of the European Union by Means of a Multifactor Algorithm. Appl. Sci. 2023, 13, 8520. https://doi.org/10.3390/app13148520
Marotta A, Porras-Amores C, Rodríguez Sánchez A, Villoria Sáez P, Masera G. Greenhouse Gas Emissions Forecasts in Countries of the European Union by Means of a Multifactor Algorithm. Applied Sciences. 2023; 13(14):8520. https://doi.org/10.3390/app13148520
Chicago/Turabian StyleMarotta, Antonio, César Porras-Amores, Antonio Rodríguez Sánchez, Paola Villoria Sáez, and Gabriele Masera. 2023. "Greenhouse Gas Emissions Forecasts in Countries of the European Union by Means of a Multifactor Algorithm" Applied Sciences 13, no. 14: 8520. https://doi.org/10.3390/app13148520
APA StyleMarotta, A., Porras-Amores, C., Rodríguez Sánchez, A., Villoria Sáez, P., & Masera, G. (2023). Greenhouse Gas Emissions Forecasts in Countries of the European Union by Means of a Multifactor Algorithm. Applied Sciences, 13(14), 8520. https://doi.org/10.3390/app13148520